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Great thanks to previous posts for the content in my file. However I'm trying to modify a double interpolation program so it only returns values within the set. Basically I want to set the minimum and maximum values to be the outermost rows/columns.
For example, if Cr is less than 0.16 and Ar is less than 0.05 i want a return of 1.95. Similarly if Cr is 1.5 and Ar is 2, I want a return of 1.40.
Your advice and suggestions in lamens terms is greatly appreciated.
The spline function to the right of the page is similar and needs the same attention however its linear interpolation so should be less complicated.
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Think the attached sheet should help. You have the choice between linear interpolation or any of the thre spline interpolations and I have implemented the limit of the argument in two different ways.
Great thanks to previous posts for the content in my file.
? Your profile says that this is your first post.
The spline function to the right of the page is similar and needs the same attention however its linear interpolation so should be less complicated.
As far as I see both, Spline() and Spline1() are identical and use lspline. lspline is a cubic spline interpolation as are pspline and cspline. The difference lies in the way the ends of the the spline segments are joined. None of the three is a linear interpolation!. If you prefer linear interpolation you should use linterp.
To limit the arguments within the range given it a series of max. 4 if conditons should do the job.
Cx has nothing to do with your question, I guess.
Think the attached sheet should help. You have the choice between linear interpolation or any of the thre spline interpolations and I have implemented the limit of the argument in two different ways.
Many thanks Werner. You are correct, I should have looked at it as simply interpolation and not a spline.
Jason Krahn wrote:
Many thanks Werner. You are correct, I should have looked at it as simply interpolation and not a spline.
Nothing wrong about spine interpolation. It depends upon your needs what fits you best.